Hello \ud83d\udc4b, <\/p>\n\n\n\n
Let’s start off by discussing how my capstone project is going so far. Fortunately, my proposed project, Foodable, got approved, and I was assigned to it with two great teammates. In short, I\u2019ve learned a lot. One of the more challenging aspects has been figuring out how to implement an efficient and highly scalable Retrieval Augmented Generation (RAG)<\/a> method. Since this is cutting-edge in today\u2019s tech stacks, there are so many ways to implement it, each with its own pros and cons. For our needs, we decided on MongoDB Atlas along with Atlas Vector Search<\/a>, paired with AWS Bedrock for embeddings and language models. This setup promises high customizability and scalability. It will certainly come with its challenges, but based on research, it should pay off in the end.<\/p>\n\n\n\n As for the capstone course itself, it\u2019s been pretty good. The course is structured in a way that assignments build on each other, which I find very effective. For example, the smaller Preliminary Design Documents, which we did individually, helped my teammates and me brainstorm and figure out the design for our application in the larger, more technical Design Document. However, a recurring issue has been due date extensions. These assignments aren\u2019t small, even the shorter ones, and they\u2019re usually due on Thursdays. But every project so far has had its deadline extended to Sunday. I think setting the due dates for Sundays from the start would align better with development sprint timelines and reduce requests for extensions.<\/p>\n\n\n\n Another exciting development in my life has been the job opportunities that have come my way since attending the OSU STEM Fair. If you haven\u2019t attended that event before, it\u2019s fantastic and packed with opportunities. Thanks to the fair, I\u2019ve had interviews with multiple companies, many of which have progressed to second-round interviews, and I\u2019m preparing for those now. Overall, my career prospects look promising, and I\u2019m excited to see what happens next. <\/p>\n\n\n\n While researching RAG methods, I encountered the term “vector embeddings”<\/a> frequently. They\u2019re essentially the foundation of how RAG methods function. Creating embeddings relies on linear algebra, and although I like math, I haven\u2019t studied beyond integral calculus since I\u2019ve been focusing on CS classes to graduate. However, I\u2019m genuinely interested in learning more about vector embeddings, semantic similarity, scalars, and related topics. Over winter break, I plan to take a freeCodeCamp course<\/a> in linear algebra to broaden my understanding of large language models and machine learning. I believe anyone interested in these technologies should have a solid grasp of linear algebra.<\/p>\n\n\n\n